Training Curriculum, Skills, and Competencies for Global Health Leaders: Good Practices and Lessons Learned.

Objectives: This paper aims to depict unique perspectives and to compare and contrast three leadership programs for global health in order to enable other training institutions to design impactful curricula. Methods: We purposively selected three global health training programs. We used a six-step curriculum development framework to systematically compare the curriculum process across programs and to identify best practices and factors contributing to the impact of each of these programs. Findings: All three fellowship programs undertook an intentional and in-depth approach to curriculum development. Each identified competencies related to leadership and technical skills. Each defined goals, though the goals differed to align with the desired impact of the program, ranging from improving the impact of HIV programming, supporting stronger global health program implementation, and supporting the next generation of global health leaders. All programs implemented the curriculum through an onboarding phase, a delivery of core content in different formats, and a wrap-up or endline phase. During implementation, each program also utilized networking and mentoring to enhance connections and to support application of learning in work roles. Programs faced overlapping challenges and opportunities including funding, strengthening partnerships, and finding ways to engage and support alumni. Conclusions: Local ownership of programs is critical, including tailoring curricula to the needs of specific contexts. Strong partnerships and resources are needed to ensure program sustainability and impact. Key Takeaways: Global health competencies and curricula should be linked to local health system needs and contexts where learners are working.Emphasizing both individualistic and collectivist approaches to learning is important in engaging and supporting diverse global health learners.Emphasizing mentorship and opportunities to apply learning in contexts where learners are working is important in order to provide support to learners as they work to integrate what they are learning into their professional roles and activities.Partnerships and resources-including donor support-are essential to implement and sustain robust leadership curricula and to provide opportunities for experiential and didactic learning.

A model for in situ plan of care for a critically unstable pediatric patient following I-131 MIBG infusion.

Recent clinical trials have moved iodine-131 (I-131) metaiodobenzylguanidine (MIBG) therapy into frontline management of high-risk neuroblastoma. With this expansion, it is reasonable to anticipate the need for intensive care level resuscitations. Radiation exposure remains the greatest risk to health care professionals managing these patients. We combined shock simulation scenario data with actual radiation dosimetry data to create a care model allowing for aggressive, prolonged in situ resuscitation of a critically ill pediatric patient after I-131 MIBG administration. This model will maintain a critical care provider's radiation level below 10% of the annual occupational dose limit (5 mSv, 500 mrem) per patient managed.

Incorporating nurse absenteeism into staffing with demand uncertainty.

Increased nurse-to-patient ratios are associated negatively with increased costs and positively with improved patient care and reduced nurse burnout rates. Thus, it is critical from a cost, patient safety, and nurse satisfaction perspective that nurses be utilized efficiently and effectively. To address this, we propose a stochastic programming formulation for nurse staffing that accounts for variability in the patient census and nurse absenteeism, day-to-day correlations among the patient census levels, and costs associated with three different classes of nursing personnel: unit, pool, and temporary nurses. The decisions to be made include: how many unit nurses to employ, how large a pool of cross-trained nurses to maintain, how to allocate the pool nurses on a daily basis, and how many temporary nurses to utilize daily. A genetic algorithm is developed to solve the resulting model. Preliminary results using data from a large university hospital suggest that the proposed model can save a four-unit pool hundreds of thousands of dollars annually as opposed to the crude heuristics the hospital currently employs.